The subjects of stochastic processes, information theory, and Lie groups are usually treated
separately from each other. This unique two-volume set presents these topics in a unified …

We present a temporal 6-DOF tracking method which leverages deep learning to achieve
state-of-the-art performance on challenging datasets of real world capture. Our method is …

Image guidance promises to improve targeting accuracy and broaden the scope of medical
procedures performed with needles. This paper takes a step toward automating the …

We present a 3D model-based visual tracking approach using edge and keypoint features in
a particle filtering framework. Recently, particle-filtering-based approaches have been …

Estimating the relative pose of a new object without prior knowledge is a hard problem,
while it is an ability very much needed in robotics and Augmented Reality. We present a …

This paper presents an approach to textureless object detection and tracking of the 3D pose.
Our detection and tracking schemes are coherently integrated in a particle filtering …

The combination of on-board sensors measurements with different statistical characteristics
can be employed in robotics for localization and control, especially in GPS-denied …

We propose a geometric method for visual tracking, in which the 2-D affine motion of a given
object template is estimated in a video sequence by means of coordinate-invariant particle …

This work investigates the problem of 6-Degrees-Of-Freedom (6-DOF) object tracking from
RGB-D images, where the object is rigid and a 3D model of the object is known. As in many …

Pose refinement is an interesting and practically relevant research direction. Pose
refinement can be used to (1) obtain a more accurate pose estimate from an initial prior (eg …